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Dr George Cushen

A Data Scientist, Vision Engineer, & Product Enthusiast

Hey!

My lifelong fascination with artificial intelligence and fashion led me to become an innovator in research on computer vision for visual clothing search and augmented reality fitting room on mobile devices.

With over 10 years of experience developing research and crafting meaningful products, I am currently pursuing my dream of reimagining retail to create a smart and personalized shopping experience.

I am also actively contributing to open source projects, and methods that I implemented are now used for popular mobile apps. In my spare time, I enjoy giving seminars on the practical applications of data science and machine learning.

Interests

Deep Learning

Computer Vision

Recommender Systems

Search & Retrieval

Augmented Reality

Education

PhD Computer Vision & Machine Learning

University of Southampton

BEng Electronic Engineering

University of Southampton

Selected Publications

Person re-identification is a critical security task for recognizing a person across spatially disjoint sensors. A practical and efficient framework is presented for mobile devices (such as Google Glass, smart phones, and autonomous vehicles) where high-level semantic soft biometrics are extracted and analysed. This mobile approach may be particularly useful for the identification of persons in areas ill-served by fixed sensors or for tasks where the sensor position and direction need to dynamically adapt to a target. Results are preliminary but encouraging, shedding light on the practical aspects of applying person identification techniques to emerging wearable mobile devices.

A mobile visual clothing search system is presented whereby a smart phone user can either choose a social networking image or capture a new photo of a person wearing clothing of interest and search for similar clothing in a large cloud-based ecommerce database. The phone's GPS location is used to re-rank results by retail store location, to inform the user of local stores where similar clothing items can be tried on.

Recent & Upcoming Talks

Learn how R Markdown and Academic can help your team write, collaborate, and publish content online and internally. Examples include a landing page and documentation site for your package, a knowledge sharing platform, or a website for your lab/team.

From mail order to becoming a world class pureplay etailer, we are reimagining retail for our 4 million annual customers. Get insight into how we are leveraging cloud GPUs for deep learning to increase discovery of relevant products and transform how data scientists accelerate research. Learn how we are evolving to embrace microservices to become more agile and foster innovative ways of getting our products, services, and experiences to customers at scale. Finally, what is the future for retail technology and has the time finally come for FPGAs?

After completing his PhD in computer vision and machine learning, George Cushen took a job as the first computer vision data scientist at the UK's second largest pureplay etailer, Shop Direct. Here, he examines the challenges and parallels between working on academic projects as a computer scientist, and working as a data scientist in a mid-size retail company. Having the opportunity to work within an agile startup-like environment within a well-established business requires breaking the habit of spending hours researching and not getting anything "done", instead working closely with stakeholders and embracing the scope for innovation in order to create practical products and services. So here are some lessons learnt about the differences between academia and industry and how to make the most out of your academic experience.